import pandas as pd

# Load the dataset
movies = pd.read_csv(r"C:\Users\lenovo\Downloads\Datasets\Datasets\movies.csv")

# Check the first few rows to understand the structure
movies.head()

# Check the columns to see what data we have
movies.columns

Index(['title_x', 'imdb_id', 'poster_path', 'wiki_link', 'title_y',
       'original_title', 'is_adult', 'year_of_release', 'runtime', 'genres',
       'imdb_rating', 'imdb_votes', 'story', 'summary', 'tagline', 'actors',
       'wins_nominations', 'release_date'],
      dtype='object')

movies['summary'].head()  

0     Indian army special forces execute a covert op...
4     Under the 'Evening Shadows'  truth often plays...
5     While fighting crimes against women in Delhi  ...
11    A coming-of-age story based on the lives of st...
15    A dynamic young entrepreneur finds herself loc...
Name: summary, dtype: object

movies.head()

	title_x	imdb_id	poster_path	wiki_link	title_y	original_title	is_adult	year_of_release	runtime	genres	imdb_rating	imdb_votes	story	summary	tagline	actors	wins_nominations	release_date	sentiment
0	Uri: The Surgical Strike	tt8291224	https://upload.wikimedia.org/wikipedia/en/thum...	https://en.wikipedia.org/wiki/Uri:_The_Surgica...	Uri: The Surgical Strike	Uri: The Surgical Strike	0	2019	138	Action|Drama|War	8.4	35112	Divided over five chapters the film chronicle...	Indian army special forces execute a covert op...	NaN	Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...	4 wins	11 January 2019 (USA)	-0.221429
1	Battalion 609	tt9472208	NaN	https://en.wikipedia.org/wiki/Battalion_609	Battalion 609	Battalion 609	0	2019	131	War	4.1	73	The story revolves around a cricket match betw...	The story of Battalion 609 revolves around a c...	NaN	Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...	NaN	11 January 2019 (India)	0.233333
2	The Accidental Prime Minister (film)	tt6986710	https://upload.wikimedia.org/wikipedia/en/thum...	https://en.wikipedia.org/wiki/The_Accidental_P...	The Accidental Prime Minister	The Accidental Prime Minister	0	2019	112	Biography|Drama	6.1	5549	Based on the memoir by Indian policy analyst S...	Explores Manmohan Singh's tenure as the Prime ...	NaN	Anupam Kher|Akshaye Khanna|Aahana Kumra|Atul S...	NaN	11 January 2019 (USA)	0.600000
3	Why Cheat India	tt8108208	https://upload.wikimedia.org/wikipedia/en/thum...	https://en.wikipedia.org/wiki/Why_Cheat_India	Why Cheat India	Why Cheat India	0	2019	121	Crime|Drama	6.0	1891	The movie focuses on existing malpractices in ...	The movie focuses on existing malpractices in ...	NaN	Emraan Hashmi|Shreya Dhanwanthary|Snighdadeep ...	NaN	18 January 2019 (USA)	0.200000
4	Evening Shadows	tt6028796	NaN	https://en.wikipedia.org/wiki/Evening_Shadows	Evening Shadows	Evening Shadows	0	2018	102	Drama	7.3	280	While gay rights and marriage equality has bee...	Under the 'Evening Shadows' truth often plays...	NaN	Mona Ambegaonkar|Ananth Narayan Mahadevan|Deva...	17 wins & 1 nomination	11 January 2019 (India)	0.000000

from textblob import TextBlob

# Define a function to get the sentiment polarity
def get_sentiment(text):
    blob = TextBlob(str(text))
    return blob.sentiment.polarity

# Apply the function to the 'description' column
movies['sentiment'] = movies['summary'].apply(get_sentiment)

# Show the updated dataset with sentiment values
movies[['title_x', 'sentiment']].head()

	title_x	sentiment
0	Uri: The Surgical Strike	-0.221429
1	Battalion 609	0.233333
2	The Accidental Prime Minister (film)	0.600000
3	Why Cheat India	0.200000
4	Evening Shadows	0.000000

import matplotlib.pyplot as plt

# Plotting sentiment distribution
plt.figure(figsize=(10,6))
plt.hist(movies['sentiment'], bins=50, color='skyblue', edgecolor='black')
plt.title('Sentiment Distribution of Movie Descriptions', fontsize=16)
plt.xlabel('Sentiment Score', fontsize=12)
plt.ylabel('Frequency', fontsize=12)
plt.show()

# Assuming you have a 'rating' column
plt.figure(figsize=(10,6))
plt.scatter(movies['imdb_rating'], movies['sentiment'], alpha=0.6, color='orange')
plt.title('Sentiment vs imdb_rating', fontsize=16)
plt.xlabel('Movie Rating', fontsize=12)
plt.ylabel('Sentiment Score', fontsize=12)
plt.show()

# Sorting movies by highest sentiment
top_positive_movies = movies.sort_values(by='sentiment', ascending=False).head(10)

# Plotting
plt.figure(figsize=(10,6))
plt.barh(top_positive_movies['title_x'], top_positive_movies['sentiment'], color='green')
plt.title('Top 10 Movies with Positive Sentiment', fontsize=16)
plt.xlabel('Sentiment Score', fontsize=12)
plt.ylabel('Movie Title', fontsize=12)
plt.show()

# Assuming there's a 'genre' column
genre_sentiment = movies.groupby('genres')['sentiment'].mean().head(20)

# Plotting average sentiment by genre
genre_sentiment.sort_values().plot(kind='barh', figsize=(10,6), color='purple')
plt.title('Average Sentiment by genres', fontsize=16)
plt.xlabel('Average Sentiment', fontsize=12)
plt.ylabel('genres', fontsize=12)
plt.show()

movies.head(2)

	title_x	imdb_id	poster_path	wiki_link	title_y	original_title	is_adult	year_of_release	runtime	genres	imdb_rating	imdb_votes	story	summary	tagline	actors	wins_nominations	release_date	sentiment
0	Uri: The Surgical Strike	tt8291224	https://upload.wikimedia.org/wikipedia/en/thum...	https://en.wikipedia.org/wiki/Uri:_The_Surgica...	Uri: The Surgical Strike	Uri: The Surgical Strike	0	2019	138	Action|Drama|War	8.4	35112	Divided over five chapters the film chronicle...	Indian army special forces execute a covert op...	NaN	Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...	4 wins	11 January 2019 (USA)	-0.221429
1	Battalion 609	tt9472208	NaN	https://en.wikipedia.org/wiki/Battalion_609	Battalion 609	Battalion 609	0	2019	131	War	4.1	73	The story revolves around a cricket match betw...	The story of Battalion 609 revolves around a c...	NaN	Vicky Ahuja|Shoaib Ibrahim|Shrikant Kamat|Elen...	NaN	11 January 2019 (India)	0.233333

pip install plotly

Requirement already satisfied: plotly in c:\users\lenovo\downloads\snscrape_project\snscrape-env\lib\site-packages (6.0.1)
Requirement already satisfied: narwhals>=1.15.1 in c:\users\lenovo\downloads\snscrape_project\snscrape-env\lib\site-packages (from plotly) (1.36.0)
Requirement already satisfied: packaging in c:\users\lenovo\downloads\snscrape_project\snscrape-env\lib\site-packages (from plotly) (25.0)
Note: you may need to restart the kernel to use updated packages.

[notice] A new release of pip is available: 24.0 -> 25.0.1
[notice] To update, run: C:\Users\lenovo\Downloads\snscrape_project\snscrape-env\Scripts\python.exe -m pip install --upgrade pip

import plotly.express as px

# Drop rows with missing required fields
movies= movies.dropna(subset=['imdb_rating', 'imdb_votes', 'wins_nominations']).head(40)

fig = px.scatter_3d(
    movies,
    x='imdb_rating',
    y='imdb_votes',
    z='wins_nominations',
    color='imdb_votes',
    hover_name='title_x',
    title='Interactive 3D Scatter: imdb_rating vs imdb_votes vs wins_nominations',
    color_continuous_scale='RdBu'
)

fig.show()

movies.head(1)

	title_x	imdb_id	poster_path	wiki_link	title_y	original_title	is_adult	year_of_release	runtime	genres	imdb_rating	imdb_votes	story	summary	tagline	actors	wins_nominations	release_date
0	Uri: The Surgical Strike	tt8291224	https://upload.wikimedia.org/wikipedia/en/thum...	https://en.wikipedia.org/wiki/Uri:_The_Surgica...	Uri: The Surgical Strike	Uri: The Surgical Strike	0	2019	138	Action|Drama|War	8.4	35112	Divided over five chapters the film chronicle...	Indian army special forces execute a covert op...	NaN	Vicky Kaushal|Paresh Rawal|Mohit Raina|Yami Ga...	4 wins	11 January 2019 (USA)

print(movies.columns)

Index(['title_x', 'imdb_id', 'poster_path', 'wiki_link', 'title_y',
       'original_title', 'is_adult', 'year_of_release', 'runtime', 'genres',
       'imdb_rating', 'imdb_votes', 'story', 'summary', 'tagline', 'actors',
       'wins_nominations', 'release_date'],
      dtype='object')

import plotly.graph_objects as go
import pandas as pd

# Filter and clean data
movies_clean = movies.dropna(subset=['imdb_rating', 'wins_nominations', 'year_of_release'])

# Create 3D box plot simulation using scatter for box outlines
fig = go.Figure()

# Box 1: imdb_rating vs year_of_release
fig.add_trace(go.Box(
    y=movies_clean['imdb_rating'],
    x=movies_clean['year_of_release'],
    name='IMDb vs Year',
    boxpoints='outliers',
    marker_color='orange'
))

# Box 2: wins_nominations vs year_of_release
fig.add_trace(go.Box(
    y=movies_clean['wins_nominations'],
    x=movies_clean['year_of_release'],
    name='Wins vs Year',
    boxpoints='outliers',
    marker_color='skyblue'
))

# Box 3: imdb_rating vs wins_nominations
fig.add_trace(go.Box(
    y=movies_clean['imdb_rating'],
    x=movies_clean['wins_nominations'],
    name='IMDb vs Wins',
    boxpoints='outliers',
    marker_color='green'
))

fig.update_layout(
    title='3D-style Box Plot of IMDb, Awards, and Year',
    xaxis_title='X Axis',
    yaxis_title='Y Axis',
    showlegend=True,
    template='plotly_dark'
)

fig.show()

import plotly.express as px
import pandas as pd

# Clean the dataset: ensure all required fields are available
movies_clean = movies.dropna(subset=['title_x', 'imdb_rating', 'wins_nominations', 'year_of_release', 'story']).tail(10)

# Create the 3D scatter plot
fig = px.scatter_3d(
    movies_clean,
    x='imdb_rating',
    y='wins_nominations',
    z='year_of_release',
    color='imdb_rating',  # color intensity based on rating
    hover_data=['title_x', 'story'],  # show title and story on hover
    title='3D Movie Visualization: Rating, Awards, and Release Year',
    labels={
        'imdb_rating': 'IMDb Rating',
        'wins_nominations': 'Wins/Nominations',
        'year_of_release': 'Release Year',
        'title_x': 'Title',
        'story': 'Story'
    },
    color_continuous_scale='Viridis'
)

fig.update_traces(marker=dict(size=5, opacity=0.8))
fig.update_layout(
    scene=dict(
        xaxis_title='IMDb Rating',
        yaxis_title='Wins/Nominations',
        zaxis_title='Year of Release'
    ),
    template='plotly_dark'
)

fig.show()